Software Dev EngineerAmazon.com Inc.
Job Summary
Join Amazons Deployment Safety team and build the intelligent systems that keep our most critical cloud infrastructure running flawlessly. As a Software Development Engineer II, youll use AI and automation to design, test, and deploy updates for EC2 Frontier with precision and scale. Youll own every stage of the development lifecyclefrom crafting AI-enhanced deployment pipelines that predict risks to creating automated testing tools that catch defects before they reach production. By integrating machine learning models to analyze deployment data and real-time monitoring to flag anomalies, youll help millions of Amazon customers rely on infrastructure thats safer, faster, and more resilient.
This role is for collaborative engineers who thrive on solving ambiguous problems, mentoring peers, and turning cutting-edge AI concepts into practical, high-impact solutions. If youre passionate about blending cloud-native engineering with intelligent automation, we want to hear from you.
#AI #MachineLearning #DeploymentSafety #Cloud #Frontier
Key job responsibilities
Collaborate with experienced cross-disciplinary Amazonians to conceive, design, and bring innovative products and services to market.
Design and build innovative technologies in a large distributed computing environment and help lead fundamental changes in the industry.
Create solutions to run predictions on distributed systems with exposure to innovative technologies at incredible scale and speed.
Build distributed storage, index, and query systems that are scalable, fault-tolerant, low cost, and easy to manage/use.
Design and code the right solutions starting with broadly defined problems.
Work in an agile environment to deliver high-quality software.
A day in the life
Your morning begins with a collaborative code reviewleveraging AI-assisted tools to provide feedback that elevates the teams code quality and readiness for deployment. After a focused standup where you align on AI-driven metrics and automation priorities, you dive into building a feature you scoped last week: writing clean, scalable code to integrate a machine learning model that predicts deployment risks. You pair with a teammate to tackle a tricky integration point, using real-time debugging tools to ensure seamless automation.
Post-lunch, you join a design review where you help streamline an architecture proposalapplying AI-first principles to simplify complexity and boost efficiency. Then, you investigate an operational metric thats flagged by your anomaly detection system, tracing it to a root cause using ML-powered correlation engines. Within hours, youve drafted a fix that not only resolves the issue but also enhances your predictive safety models.
Your day balances deep, heads-down coding on cloud-native features with cross-functional problem-solvingall while driving operational excellence and mentoring peers. Every task you tackle reinforces our mission: building smarter, safer systems that millions of Amazon customers rely on daily.
This role is for collaborative engineers who thrive on solving ambiguous problems, mentoring peers, and turning cutting-edge AI concepts into practical, high-impact solutions. If youre passionate about blending cloud-native engineering with intelligent automation, we want to hear from you.
#AI #MachineLearning #DeploymentSafety #Cloud #Frontier
Key job responsibilities
Collaborate with experienced cross-disciplinary Amazonians to conceive, design, and bring innovative products and services to market.
Design and build innovative technologies in a large distributed computing environment and help lead fundamental changes in the industry.
Create solutions to run predictions on distributed systems with exposure to innovative technologies at incredible scale and speed.
Build distributed storage, index, and query systems that are scalable, fault-tolerant, low cost, and easy to manage/use.
Design and code the right solutions starting with broadly defined problems.
Work in an agile environment to deliver high-quality software.
A day in the life
Your morning begins with a collaborative code reviewleveraging AI-assisted tools to provide feedback that elevates the teams code quality and readiness for deployment. After a focused standup where you align on AI-driven metrics and automation priorities, you dive into building a feature you scoped last week: writing clean, scalable code to integrate a machine learning model that predicts deployment risks. You pair with a teammate to tackle a tricky integration point, using real-time debugging tools to ensure seamless automation.
Post-lunch, you join a design review where you help streamline an architecture proposalapplying AI-first principles to simplify complexity and boost efficiency. Then, you investigate an operational metric thats flagged by your anomaly detection system, tracing it to a root cause using ML-powered correlation engines. Within hours, youve drafted a fix that not only resolves the issue but also enhances your predictive safety models.
Your day balances deep, heads-down coding on cloud-native features with cross-functional problem-solvingall while driving operational excellence and mentoring peers. Every task you tackle reinforces our mission: building smarter, safer systems that millions of Amazon customers rely on daily.